Estimation of speed, stator temperature and rotor temperature in cage induction motor drive using the extended Kalman filter algorithm

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Estimation of speed, stator temperature and rotor temperature in cage induction motor drive using the extended Kalman filter algorithm

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Application of the extended Kalman filter (EKF) algorithm to the estimation of speed, stator temperature and rotor temperature in induction motor drives is described. The estimation technique is based on a closed-loop observer that incorporates mathematical models of the electrical, mechanical and thermal processes occurring within the induction motor. Speed and temperature estimation is independent of the drive's operating mode, though closed-loop estimation is possible only if stator currents are nonzero. The EKF algorithm used to perform the estimation process has been implemented using a TMS320C30 digital signal processor and experimental results demonstrate the effectiveness of the new estimation algorithm.

Inspec keywords: squirrel cage motors; closed loop systems; parameter estimation; stators; induction motor drives; rotors; digital signal processing chips; Kalman filters; observers

Other keywords: closed-loop estimation; cage induction motor drive; extended Kalman filter algorithm; stator temperature estimation; mathematical models; TMS320C30 digital signal processor; nonzero stator currents; mechanical processes; electrical processes; closed-loop observer; thermal processes; rotor temperature estimation; speed estimation

Subjects: Simulation, modelling and identification; Drives; Digital signal processing; Asynchronous machines; Digital signal processing chips; Signal processing and detection

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